There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Climate change 2014 - Synthesis Report

This book introduces the key stages of niche- based habitat suitability model building, evaluation and prediction required for understanding and predicting future patterns of species and biodiversity. Beginning with the main theory behind ecological niches and species distributions, the book proceeds through all major steps of model building, from conceptualization and model training to model evaluation and spatio- temporal predictions. Extensive examples using R support graduate students and researchers in quantifying ecological niches and predicting species distributions with their own data, and help to address key environmental and conservation problems. Reflecting this highly active field of research, the book incorporates the latest developments from informatics and statistics, as well as using data from remote sources such as satellite imagery. A website at www.unil.ch/ hsdm contains the codes and supporting material required to run the examples and teach courses. All three authors are recognized specialists of and have contributed substantially to the development of spatial prediction methods for species’ habitat suitability and distribution modeling. They published a large number of papers, overall cumulating tens of thousands of citations, and are ISI Highly Cited Researchers.

Habitat Suitability and Distribution Models

Remote sensing for conservation monitoring: Assessing protected areas, habitat extent, habitat condition, species diversity, and threats

Crop evapotranspiration estimation with FAO56: Past and future

The sustainable conservation of mountain semi-natural meadows depends on the knowledge of their vegetation dynamics and management practices. Time series of vegetation indices (VI) derived from high temporal resolution satellite images can be a useful tool to the sustainable management of semi-natural meadows ecosystem and grazing activities. In this study satellite VI from the Moderate Resolution Imaging Spectroradiometer (MODIS) are evaluated against in situ measurements of VIs and plant height in the semi-natural mountain meadows of Northeast Portugal. In two testes sites, we evaluated the performance of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from MODIS and field spectroradiometer sensor in characterizing semi-natural meadows phenology and plant height. The Savitzky-Golay filter was used for smoothing each VI time series, as well as to extract a number of NDVI and EVI metrics by computing derivatives. There was weak to reasonable agreement between VIs-metrics from MODIS and ground based derived phenology. The NDVI had a great sensitivity to crop growth changes during start of growth season, whereas the EVI exhibited more sensitivity at the pick of the maximum green biomass. The relationship between vegetation height and both VI from MODIS or field spectroradiometer, fit a non-linear model with similar pattern function for each test site. Regression analysis revealed that 67% of the in-season plant height variability could be explained by MODIS EVI . These results suggest a great sensibility of MODIS EVI to detect the phenology and plant height of semi-natural meadows, even in situations of high plant height.

/pdf/evaluating-modis-vegetation-indices-using-ground-based-ccssn39bgn.pdf

Evaluating MODIS vegetation indices using ground based measurements in mountain semi-natural meadows of Northeast Portugal

“Lameiros” are ancestral semi-natural meadows, essential elements of mountain landscapes in Northern Portugal In the “lameiros” a traditional irrigation system is used and water is applied all year around They are mainly used for forage production for autochthonous bovine feeding, but they are also important for the water and nutrients cycle regulation, erosion control and as barrier to forest fires propagation Although recognized for their economical, environmental, landscaping, cultural and genetic value, the perpetuation of these “lameiros” could be at risk, at medium term, due to human desertification in the mountain regions and to the announced constraints in use of water resources To preserve these landscapes it is essential to know them better and to better characterize them Therefore a monitoring program using remote sensing tools is now being developed to evaluate different patterns of “lameiros”, and their spatial extent and evolution Two important questions are determinant in this program: the selection of the most appropriate spatial resolution for monitoring “lameiros”, and the availability of satellite historical data In this context, NDVI were compared in two selected test sites, with and without full irrigation Data were derived from several field campaigns with a spectroradiometer and using different sensors: i) Landsat 5 and Landsat 7 (30m pixel), ii) SPOT 4 and SPOT 2 (20m pixel), iii) SPOT 5 (10m pixel) The NDVI temporal series produced were evaluated considering “lameiros” management and weather data Results obtained so far indicate that the SPOT images provide data at the most adequate scale

https://www.fc.up.pt/pessoas/andre.marcal/papers/EARSeL2008_102.pdf

Remote sensing monitoring to preserve ancestral semi-natural mountain meadows landscapes

Canopy VIS-NIR spectroscopy and self-learning artificial intelligence for a generalised model of predawn leaf water potential in Vitis vinifera

The growth in data availability and in the number of users from non-spatial disciplines has increased the concern with spatial data management and spatial data quality. This reality contextualizes the need and importance of data quality management throughout the spatial data cycle related to data editing and sharing in the context of knowledge networks. The development of standard concepts, procedures and tools may foster important advances in the improvement of spatial dataset production, use and management practices. The implementation of environmental monitoring programs implies a growing number and diversity of users with specific capabilities and responsibilities. In this context, spatial data quality evaluation and management promotes communication, optimizes processes of analysis and spatial modelling, and in this sense improves research and political and technical decisionmaking and action. This paper focuses on the methods and tools currently available to evaluate the external quality of datasets for environmental and ecological monitoring. A novel framework is presented that allows integrating and interconnecting spatial data quality evaluation with metadata geoportals in WebGIS platforms, facilitating evaluation by users with often limited expertise in this field. The advances achieved in this research highlight the relevance of developing capacities for different users to improve data collection, data models, spatial data processing and modelling, but also the need to inform and report on spatial data quality using adequate tools.

/pdf/novel-tools-to-improve-the-management-of-spatial-data-3uuz5sugg7.pdf

Isabel Pôças

Papers

Evaluating MODIS vegetation indices using ground based measurements in mountain semi-natural meadows of Northeast Portugal

Remote sensing monitoring to preserve ancestral semi-natural mountain meadows landscapes

Canopy VIS-NIR spectroscopy and self-learning artificial intelligence for a generalised model of predawn leaf water potential in Vitis vinifera

Novel Tools to Improve the Management of Spatial Data Quality in the Context of Ecosystem and Biodiversity Monitoring

Will climate change drive alien invasive plants into high nature value areas? An improved model-based regional assessment in the North of Portugal